Machine Learning Engineer

Hoomanely; Bengaluru; On-site; INR 1,400,000 - 2,400,000; Full time

Job summary

Hoomanely in Bengaluru is seeking a hands-on ML engineer to build and ship models across its sensor-driven product ecosystem, working closely with the ML Lead on DSP, computer vision, and time series problems.

You will take models from prototype to production, build data pipelines, deploy on edge hardware with latency considerations, and collaborate with firmware, hardware, and app teams to turn model outputs into actionable insights.

Qualifications

• 3+ years of experience
• B.Tech from a Tier 1 Institute

Responsibilities

• Build and iterate on ML models for time series, audio signal, and sensor fusion problems, under the guidance of the ML Lead
• Build and maintain data preprocessing and feature engineering pipelines that prepare sensor data for training and inference at scale
• Package and deploy models into production, including on edge or embedded compute, with attention to latency and resource constraints
• Run structured experiments to evaluate model accuracy, generalization, and failure modes, and document findings clearly
• Support monitoring and retraining pipelines that track model performance and drift after deployment
• Work closely with firmware, hardware, and app teams to turn model outputs into clear, actionable product insight

Skills

3+ years of experience

Education

B.Tech from a Tier 1 Institute

Job description

We're looking for a hands-on ML engineer to build and ship models across Hoomanely's sensor-driven product ecosystem, working closely with the ML Lead on digital signal processing, computer vision, and time series problems. You're comfortable taking a model from an early prototype through to a reliable, production-deployed system.

What You'll Do

• Build and iterate on ML models for time series, audio signal, and sensor fusion problems, under the guidance of the ML Lead
• Build and maintain data preprocessing and feature engineering pipelines that prepare sensor data for training and inference at scale
• Package and deploy models into production, including on edge or embedded compute, with attention to latency and resource constraints
• Run structured experiments to evaluate model accuracy, generalization, and failure modes, and document findings clearly
• Support monitoring and retraining pipelines that track model performance and drift after deployment
• Work closely with firmware, hardware, and app teams to turn model outputs into clear, actionable product insight

Required Qualifications

• 3+ years of experience
• B.Tech from a Tier 1 Institute

Why Join Us?

• Ship models that run on real hardware, on real dogs — not just in a notebook
• Learn directly from the ML Lead while owning real pieces of the roadmap
• Take ownership early, with a direct line to the people building the rest of the product
• Join a small, fast-moving team building a category-defining, sensor-driven product